The Relation Between Conditionally Heteroskedastic Factor Models amd Factor GARCH Models

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The Relation Between Conditionally Heteroskedastic Factor Models amd Factor GARCH Models

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Sentana, E.

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Enrique Sentana

Abstract

The factor GARCH model of Engle (1987) and the latent factor ARCH model of Diebold and Nerlove (1989) have become rather popular multivariate volatility parameterizations due to their parsimony, and the commonality in volatility movements across different financial series. Nevertheless, there is some confusion in the literature between them. The purpose of this note is to make clear their similarities and differences by providing a formal nesting of the two models, which can be exploited to analyze their statistical features in a more general context. At the same time, their differences may be important in the interpretation of empirical results.

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Paper provided by Centro de Estudios Monetarios Y Financieros- in its series Papers with number 9719.

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Length: 14 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:fth:cemfdt:9719

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Article
- Enrique Sentana, 1998. "The relation between conditionally heteroskedastic factor models and factor GARCH models," Econometrics Journal, Royal Economic Society, vol. 1(RegularPa), pages 1-9.

Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C6 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming

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Enrique Sentana, 2000. "The Likelihood Function of Conditionally Heteroskedastic Factor Models," Annales d'Economie et de Statistique, ADRES, issue 58, pages 02, Avril-Jui. [Downloadable!]
Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation Of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI. [Downloadable!]
Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109. [Downloadable!]
Other versions:
- BAUWENS, Luc & LAURENT, SŽbastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," CORE Discussion Papers 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
Elena Andreou & Eric Ghysels, 2003. "Test for Breaks in the Conditional Co-Movements of Asset Returns," University of Cyprus Working Papers in Economics 3-2003, University of Cyprus Department of Economics. [Downloadable!]
Other versions:
- Elena Andreou & Eric Ghysels, 2002. "Tests for Breaks in the Conditional Co-movements of Asset Returns," CIRANO Working Papers 2002s-59, CIRANO. [Downloadable!]
Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Generalized Dynamic Factor Model + GARCH
Exploiting Multivariate Information for Univariate Prediction," LEM Papers Series 2006/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
Paolo Zaffaroni, 2000. "Contemporaneous Aggregation of GARCH Processes," STICERD - Econometrics Paper Series /2000/378, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Multivariate GARCH models," CREATES Research Papers 2008-06, School of Economics and Management, University of Aarhus. [Downloadable!]
Other versions:
- Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008. [Downloadable!]
Catherine Doz & Éric Renault, 2004. "Conditionally Heteroskedastic Factor Models: Identification and Instrumental Variables Estimation," CIRANO Working Papers 2004s-37, CIRANO. [Downloadable!]
Catherine Doz & Eric Renault, 2004. "Conditionaly Heteroskedastic Factor Models : Identificationand Instrumental variables Estmation," THEMA Working Papers 2004-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise. [Downloadable!]

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